A small open-source LLM, trained on a GPT-4-generated synthetic agent dataset, can run a unified retrieval loop that answers both single-hop and multi-hop questions at near GPT-4 levels.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Agent-UniRAG: A Trainable Open-Source LLM Agent Framework for Unified Retrieval-Augmented Generation Systems
A small open-source LLM, trained on a GPT-4-generated synthetic agent dataset, can run a unified retrieval loop that answers both single-hop and multi-hop questions at near GPT-4 levels.